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LAESI mass spectrometry imaging as a tool to differentiate the root metabolome of native and range-expanding plant species.

Purva KulkarniRutger A WilschutKoen J F VerhoevenWim H van der PuttenPaolina Garbeva
Published in: Planta (2018)
LAESI-MSI, an innovative high-throughput technique holds a unique potential for untargeted detection, profiling and spatial localization of metabolites from intact plant samples without need for extraction or extensive sample preparation. Our understanding of chemical diversity in biological samples has greatly improved through recent advances in mass spectrometry (MS). MS-based-imaging (MSI) techniques have further enhanced this by providing spatial information on the distribution of metabolites and their relative abundance. This study aims to employ laser-ablation electrospray ionization (LAESI) MSI as a tool to profile and compare the root metabolome of two pairs of native and range-expanding plant species. It has been proposed that successful range-expanding plant species, like introduced exotic invaders, have a novel, or a more diverse secondary chemistry. Although some tests have been made using aboveground plant materials, tests using root materials are rare. We tested the hypothesis that range-expanding plants possess more diverse root chemistries than native plant species. To examine the root chemistry of the selected plant species, LAESI-MSI was performed in positive ion mode and data were acquired in a mass range of m/z 50-1200 with a spatial resolution of 100 µm. The acquired data were analyzed using in-house scripts, and differences in the spatial profiles were studied for discriminatory mass features. The results revealed clear differences in the metabolite profiles amongst and within both pairs of congeneric plant species, in the form of distinct metabolic fingerprints. The use of ambient conditions and the fact that no sample preparation was required, established LAESI-MSI as an ideal technique for untargeted metabolomics and for direct correlation of the acquired data to the underlying metabolomic complexity present in intact plant samples.
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